AWS Machine Learning Blog

This is a guest post co-written by Sergio Delgado from YoucanBook.me. In their own words, “YouCanBook.me is a small, independent and fully remote team, who love solving scheduling problems all over the world.” At YoucanBook.me, we like to say that we’re “a small company that does great things.” Many aspects of our day-to-day culture are […]

This post is co-written by Femi Olumofin, an analytics architect at Infoblox. In the same way that you can conveniently recognize someone by name instead of government-issued ID or telephone number, the Domain Name System (DNS) provides a convenient means for naming and reaching internet services or resources behind IP addresses. The pervasiveness of DNS, […]

In this post, we demonstrate how to use Amazon Comprehend Medical to extract medication names and medical conditions to monitor drug safety and adverse events. Amazon Comprehend Medical is a natural language processing (NLP) service that uses machine learning (ML) to easily extract relevant medical information from unstructured text. We query the OpenFDA API (an open-source API published by […]

­ This is a guest post by AWS Machine Learning Hero Cyrus Wong. Staying connected with family, friends, and colleagues is easy for most people who live with or close to others. For educators who need to communicate lessons and schedules with their students, or businesses who communicate with new and existing customers, staying connected […]

November 2022: The solution described here is not the latest best practice. The new HuggingFace Deep Learning Container (DLC) is available in Amazon SageMaker (see Use Hugging Face with Amazon SageMaker). For customer training BERT models, the recommended pattern is to use HuggingFace DLC, shown as in Finetuning Hugging Face DistilBERT with Amazon Reviews Polarity dataset. […]

In October 2019, AWS announced that it was working with Facebook, Microsoft, and the Partnership on AI on the first Deepfake Detection Challenge. Deepfake algorithms are the same as the underlying technology that has given us realistic animation effects in movies and video games. Unfortunately, those same algorithms have been used by bad actors to […]

April 2023 Update: Starting January 31, 2024, you will no longer be able to access AWS DeepLens through the AWS management console, manage DeepLens devices, or access any projects you have created. To learn more, refer to these frequently asked questions about AWS DeepLens end of life. Working from home can be a big change to […]

AWS DeepRacer is a fully autonomous 1/18th scale race car powered by reinforcement learning (RL) that gives machine learning (ML) developers of all skill levels the opportunity to learn and build their ML skills in a fun and competitive way. AWS DeepRacer Evo includes new features and capabilities to help you learn more about ML […]

Convolutional neural networks (CNNs) achieve state-of-the-art results in tasks such as image classification and object detection. They are used in many diverse applications, such as in autonomous driving to detect traffic signs and objects on the street, in healthcare to more accurately classify anomalies in image-based data, and in retail for inventory management. However, CNNs […]

Update Sep 28, 2020 – New features: Amazon Comprehend custom entity recognition real-time endpoints now supports application auto scaling. Please refer to the section Auto Scaling with real-time endpoints in this post to learn more. Update Aug 12, 2020 – New features: Amazon Comprehend adds five new languages(Spanish, French, German, Italian and Portuguese) read here. Amazon […]